{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Driver Comfort Analysis\n",
    "\n",
    "## Introduction\n",
    "\n",
    "This example will demonstrate how to use the Inertial Measurement Unit to do a simple analysis for driver comfort while driving. An IMU is a sensor that measures rotational acceleration and forces at a certain point in the vehicle. BeamNGpy provides a simulated version of such a sensor that can be placed in or on the vehicle. Contrary to real IMUs, BeamNG's are completely size and weightless, meaning they have no effect on the behavior of the vehicle and an arbitrary amount of them can be added.\n",
    "\n",
    "## Scenario \n",
    "\n",
    "Our scenario contains two vehicles that are tasked with driving to a certain waypoint on the map using BeamNG's AI. The AI will be given different speed levels and aggression values. Both vehicles are equipped with an IMU placed at the headrest of the driver's seat, giving measurements about rotational acceleration and forces acting on the driver. After both vehicles arrive at their destination, the data measured for both will be plotted for comparison.\n",
    "\n",
    "## Setup\n",
    "\n",
    "Setting up the environment starts with importing the required classes, mainly:\n",
    "\n",
    "* `BeamNGpy`: The backbone of the library used to manage BeamNG and communicate with the running simulation\n",
    "* `Scenario`: A class representing the scenario we set up. It will contain information about which level to load and vehicles contained in the scenario.\n",
    "* `Vehicle`: Each of our vehicles will be an instance of this class. It is used to represent and communicate with a vehicle in the simulation.\n",
    "* `IMU`: The class implementing an IMU sensor and focus of this example. Each vehicle will have an instance of this to gather measurements.\n",
    "\n",
    "Instances of these classes are compiled into one scenario that will then be loaded in the simulator.\n",
    "\n",
    "Additionally, some modules and classes related to later plotting are imported."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "from beamngpy import BeamNGpy, Vehicle, Scenario\n",
    "from beamngpy.sensors import IMU\n",
    "\n",
    "sns.set()  # Let seaborn apply better styling to all matplotlib graphs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The actual scenario will be set up by instantiating the `Scenario` class with an instance set on `west_coast_usa` that we name \"driver_comfort\". Two instances of the `Vehicle` class will be created using the ETK800 model and given unique names for later reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "beamng = BeamNGpy('localhost', 64256)\n",
    "beamng.open()\n",
    "\n",
    "scenario = Scenario('west_coast_usa', 'driver_comfort')\n",
    "\n",
    "careful = Vehicle('careful', model='etk800', licence='CAREFUL', colour='Green')\n",
    "aggressive = Vehicle('aggressive', model='etk800', licence='AGGRO', colour='Red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With two vehicles instantiated we move on to creating IMU sensor objects. These objects are placed at locations *relative to the vehicle's origin*. This means an IMU placed at (0, 0, 0) is always at the vehicle's origin, regardless of its position in the world. This, however, means placement of the IMU is best done by looking at node positions in the game's vehicle editor to get reference values. For the creation of this example, the game was started manually and the location for IMUs was determined by looking at relative node positions close to the driver's headrest of the ETK800 vehicle.\n",
    "\n",
    "**Note**: The `debug=True` flag passed to the IMUs has no effect on the data. It merely enables debug visualization of the IMU an its readings in game."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "careful_imu = IMU(pos=(0.73, 0.51, 0.8), debug=True)\n",
    "careful.attach_sensor('careful_imu', careful_imu)\n",
    "\n",
    "aggressive_imu = IMU(pos=(0.73, 0.51, 0.8), debug=True)\n",
    "aggressive.attach_sensor('aggressive_imu', aggressive_imu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we add the vehicles to our scenario. The locations they are placed were determined manually in the game's World Editor. The call to `scenario.make(beamng)` creates files necessary for the game to load our scenario during the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "scenario.add_vehicle(careful, pos=(-767.1, 402.8, 142.8), rot_quat=(0, 0, 0.027, 1))\n",
    "scenario.add_vehicle(aggressive, pos=(-770.1, 398.8, 142.8), rot_quat=(0, 0, 0.027, 1))\n",
    "\n",
    "scenario.make(beamng)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We further set up two lists that will contain measurement data for both vehicles. These will later be put into a Pandas `DataFrame` for easy data analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "careful_data = []\n",
    "aggressive_data = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running\n",
    "\n",
    "After our scenario is loaded in the simulator, we start the scenario letting the aggressive vehicle drive to its destination first, using a high maximum speed and high aggression value. Data from the vehicle's IMU is gathered every 30 frames for 1800 frames. Afterwards, the careful vehicle is given the same destination but a lower speed limit and lower aggression value. Its IMU will be sampled in the same manner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "beamng.load_scenario(scenario)\n",
    "beamng.set_deterministic()\n",
    "beamng.set_steps_per_second(60)\n",
    "beamng.start_scenario()\n",
    "beamng.pause()\n",
    "\n",
    "beamng.switch_vehicle(aggressive)  # Switches the game's focus to the aggressive vehicle. No effect besides making it easier to watch.\n",
    "\n",
    "aggressive.ai_set_waypoint('junction1_wp24')\n",
    "aggressive.ai_set_speed(50, mode='limit')\n",
    "aggressive.ai_set_aggression(1)\n",
    "beamng.step(240)  # Give the vehicle some frames to get going\n",
    "\n",
    "for t in range(0, 1800, 30):\n",
    "    aggressive.poll_sensors()\n",
    "    row = aggressive_imu.data\n",
    "    row = [\n",
    "        t,\n",
    "        'aggressive',\n",
    "        row['aX'],\n",
    "        row['aY'],\n",
    "        row['aZ'],\n",
    "        row['gX'],\n",
    "        row['gY'],\n",
    "        row['gZ'],\n",
    "    ]\n",
    "    aggressive_data.append(row)\n",
    "    bng.step(30)\n",
    "\n",
    "aggressive.ai_set_waypoint('tunnel_NE_A_1')  # Make it move away to make room for the careful car\n",
    "\n",
    "beamng.switch_vehicle(careful)  # Switches the game's focus to the careful vehicle. No effect besides making it easier to watch.\n",
    "\n",
    "careful.ai_set_waypoint('junction1_wp24')\n",
    "careful.ai_set_speed(10, mode='limit')\n",
    "careful.ai_set_aggression(0.3)\n",
    "beamng.step(240)\n",
    "\n",
    "for t in range(0, 1800, 30):\n",
    "    careful.poll_sensors()\n",
    "    row = careful_imu.data\n",
    "    row = [\n",
    "        t,\n",
    "        'careful',\n",
    "        row['aX'],\n",
    "        row['aY'],\n",
    "        row['aZ'],\n",
    "        row['gX'],\n",
    "        row['gY'],\n",
    "        row['gZ'],\n",
    "    ]\n",
    "    careful_data.append(row)\n",
    "    beamng.step(30)\n",
    "\n",
    "data = careful_data + aggressive_data\n",
    "df = pd.DataFrame(data, columns=['T', 'Behavior', 'aX', 'aY', 'aZ', 'gX', 'gY', 'gZ'])\n",
    "\n",
    "beamng.close()  # Close beamng as all data was gathered"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis\n",
    "\n",
    "We analyze the data by computing the respective lengths of rotational acceleration and force vectors on each vehicle. This data is then aggregated into minimum, maximum, and mean lengths to compare both careful and aggressive measurements and later plotted to display the length of each measurement over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Force</th>\n",
       "      <th colspan=\"3\" halign=\"left\">Rotation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>mean</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Behavior</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>aggressive</th>\n",
       "      <td>1.191223</td>\n",
       "      <td>252.030389</td>\n",
       "      <td>24.134084</td>\n",
       "      <td>0.002187</td>\n",
       "      <td>0.897925</td>\n",
       "      <td>0.133496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>careful</th>\n",
       "      <td>1.611150</td>\n",
       "      <td>47.699224</td>\n",
       "      <td>12.119462</td>\n",
       "      <td>0.000748</td>\n",
       "      <td>0.198128</td>\n",
       "      <td>0.041694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Force                         Rotation                    \n",
       "                 min         max       mean       min       max      mean\n",
       "Behavior                                                                 \n",
       "aggressive  1.191223  252.030389  24.134084  0.002187  0.897925  0.133496\n",
       "careful     1.611150   47.699224  12.119462  0.000748  0.198128  0.041694"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Force'] = df.apply(lambda r: np.linalg.norm([r['gX'], r['gY'], r['gZ']]), axis=1)\n",
    "df['Rotation'] = df.apply(lambda r: np.linalg.norm([r['aX'], r['aY'], r['aZ']]), axis=1)\n",
    "df[['Behavior', 'Force', 'Rotation']].groupby('Behavior').agg(['min', 'max', 'mean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='T', ylabel='Rotation'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure, ax = plt.subplots(2, 1, figsize=(30, 15))\n",
    "pal = {'aggressive': '#FF4444', 'careful': '#22FF22'}\n",
    "sns.lineplot(x='T', y='Force', hue='Behavior', data=df, palette=pal, ax=ax[0])\n",
    "sns.lineplot(x='T', y='Rotation', hue='Behavior', data=df, palette=pal, ax=ax[1])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
